Georgia Tech Research Featured at SIAM CSE13

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Joshua Preston

Communications Officer

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Georgia Tech researchers are taking part in SIAM CSE13 in Boston, Mass., Feb. 24 - March 1, through a number of technical talks and panels.

Georgia Tech researchers are taking part in SIAM CSE13 in Boston, Mass., Feb. 24 - March 1, through a number of technical talks and panels. The SIAM CSE conference seeks to enable in-depth technical discussions on a wide variety of major computational efforts on large problems in science and engineering, foster the interdisciplinary culture required to meet these large-scale challenges, and promote the training of the next generation of computational scientists.

Below is a synopsis of Georgia Tech researchers participating and their research topics. Details can be found at the technical program schedule.


Georgia Tech @ SIAM CSE13

Panel Discussion: Big Data Meets Big Models

Panelist: David A. Bader

Minisymposium: Frontiers in Large-Scale Graph Analysis

Organizers: Jason Riedy, Henning Meyerhenke, David A. Bader

Talks:

MS25

Classifying Soft Error Vulnerabilities in Extreme-Scale Scientific Applications Using Bifit

Authors: Jeffrey S. Vetter, Dong Li (Oak Ridge), Weikuan Yu (Auburn U)

MS141

Applications and Challenges in Large-scale Graph Analysis

Authors: David A. Bader, Jason Riedy, Henning Meyerhenke

MS152

Large-scale Biomolecular Electrostatics with Massively Parallel FMM

Author: Aparna Chandramowlishwaran

MS179

Analyzing Graph Structure in Streaming Data with STINGER

Authors: Jason Riedy, David A. Bader, Robert C. McColl, David Ediger

MS195

Tensor Hypercontraction Theory: A Physically-Motivated Rank Reduction Method for Electronic Structure Theory

Author: Robert M. Parrish

MS199

On the Consistency of Calibration Parameter Estimation in Deterministic Computer Experiments

Author: Jeff Wu

MS225

PASQUAL: Parallel Techniques for Next Generation Genome Sequence Assembly

Authors: Xing Liu, Pushkar Pande, Henning Meyerhenke, David A. Bader

MS231

A ’Roofline’ Model of Energy and What it Implies for Algorithm Design

Author: Jee Whan Choi, Rich Vuduc

Additional Information

Groups

High Performance Computing (HPC)

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Data Engineering and Science
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Status
  • Created By: Joshua Preston
  • Workflow Status: Published
  • Created On: Feb 27, 2013 - 1:26pm
  • Last Updated: Oct 7, 2016 - 11:13pm